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Build a Python-based blog post generator

Creating a Python-based blog post generator involves combining a few key components: input handling (for the title or topic), content generation (using an NLP model or template-based approach), and output formatting. Here’s a straightforward example using the OpenAI GPT API for generating unique SEO-friendly articles from titles you provide.

This example assumes you have access to OpenAI’s API and will use the openai Python package. If you want a purely local solution, you’d need to rely on templates or a fine-tuned model you host yourself.


python
import openai openai.api_key = "YOUR_OPENAI_API_KEY" def generate_blog_post(title, max_words=1800, min_words=1500): prompt = ( f"Write a unique, SEO-friendly blog post of about {min_words}-{max_words} words " f"based on this title: '{title}'. The article should be detailed, well-structured, " f"and avoid starting directly with the title itself." ) response = openai.ChatCompletion.create( model="gpt-4o-mini", messages=[ {"role": "system", "content": "You generate detailed SEO-friendly blog articles."}, {"role": "user", "content": prompt} ], max_tokens=3000, # Adjust for length if needed temperature=0.7, top_p=1, frequency_penalty=0, presence_penalty=0 ) article = response['choices'][0]['message']['content'] return article if __name__ == "__main__": title = input("Enter the blog post title: ") post = generate_blog_post(title) print(post)

How it works:

  • You input a blog post title.

  • The prompt instructs GPT to generate a unique SEO-friendly article between 1500-1800 words.

  • The system message sets the context for SEO-friendly content.

  • The script prints the resulting article in the console.


If you want to expand this:

  • Save generated posts to files.

  • Batch generate multiple posts.

  • Add more prompt engineering to control tone, style, or structure.

Would you like me to help build any of those features or a version without API calls?

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